Domain-independent method of detecting inconsistencies in SBVR-based business rules

Pavan Kumar Chittimalli, Kritika Anand
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引用次数: 13

Abstract

Traditionally, business rules are expressed informally in English, captured eventually, as a part of UML use-cases. Detecting anomalies in business rules is extremely difficult to automate, due to their informal nature, and manually error-prone due to the size and complexity. In recent times, business rules are being expressed increasingly using standard representations (such as Semantics of Business Vocabularies and Rules (SBVR)). We present a method to detect inconsistencies amongst the rules, based on the model checking. We exploit the First Order Logic (FOL) basis of SBVR representation to propose a method that is independent of the business domain. We present a case-study of business rules for well-known example of car-rental, and our method shows promising results to detect inconsistencies.
在基于sbvr的业务规则中检测不一致性的独立于域的方法
传统上,业务规则是用英语非正式地表示的,最终作为UML用例的一部分被捕获。检测业务规则中的异常非常难以自动化,因为它们是非正式的,并且由于其大小和复杂性,人工容易出错。最近,业务规则越来越多地使用标准表示(例如业务词汇表和规则语义(SBVR))来表示。提出了一种基于模型检查的规则不一致性检测方法。我们利用SBVR表示的一阶逻辑(FOL)基础提出了一种独立于业务领域的方法。我们给出了一个众所周知的汽车租赁业务规则的案例研究,我们的方法在检测不一致性方面显示出很好的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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